Human health risk from manganese in groundwater
Machine learning is the key to uncovering where populations across the globe are at risk from manganese in their groundwater-sourced drinking water.
Nature Water↗
Geology topics
Katherine J. Knierim
Publications and source records attributed to Katherine J. Knierim.
Groundwater salinity: Applying the specific conductance and water type proxy
Groundwater is increasingly needed for water supplies but may have limited utility in some locations because of its salinity. Salinity, often expressed as total dissolved solid (TDS), is frequently estimated using specific conductance (SC) measurements. However, the commonly used proxy (0.65 multiplied by SC to indicate TDS, common in many handheld meters) can result in inaccurate TDS estimates. First, the TDS–SC relationship is not linear over the entire concentration range of groundwater. Furthermore, the TDS (and salinity)–SC relationships vary substantially depending on the major-ion composition. Here we develop a proxy method utilizing SC and major-ion water type to estimate TDS and salinity specifically for groundwaters. Compared to most surface waters, groundwater tends to have a wider range of salinity (fresh to highly saline) and higher concentrations of bedrock-derived solutes such as carbonate ions, silica, and many other ions. The dataset used to develop the proxies includes water chemistry data from 149,059 discrete groundwater samples. The groundwater proxies, which employ nonlinear log–log relations, utilize five water types (HCO 3 , Cl, Ca-Mg-SO 4 , Na-K-SO 4 , and mixed waters), are accurate (median percent difference between TDS and salinity determined using the proxy compared to discrete measurements was <±0.8%) over a wide range of SC (up to 200 mS/cm), rapid, cost-effective, and can be measured on-site.
Groundwater↗
Groundwater age estimates for the Mississippi River Valley alluvial aquifer based on tracer data collected during 2018–20
This study characterized groundwater age across the Mississippi River Valley alluvial aquifer (MRVA). Groundwater samples from 69 MRVA wells and 19 wells in Tertiary units of the Mississippi embayment aquifer system (MEAS) were analyzed for sulfur hexafluoride (SF 6 ), tritium ( 3 H), helium (He), and (or) carbon-14 of dissolved inorganic carbon ( 14 C). The age distributions of 89 samples were estimated by fitting lumped parameter models to processed tracer concentrations with the U.S. Geological Survey software TracerLPM. Mean ages of MRVA groundwater samples ranged from 12 to 22,000 years, with a median of 140 years. Mean ages of MEAS groundwater samples ranged from 230 to 52,000 or more years, with a median of 13,500 years. The spatial distribution of MRVA groundwater ages was found to be influenced by depth, inflow of groundwater from deeper units, and soil saturated hydraulic conductivity. In parts of the MRVA, the spatial distribution of MRVA groundwater ages was found to be influenced by annual recharge and (or) annual groundwater pumpage.
Alabama, Arkansas, Illinois, Kentucky, Louisiana, ↗
Status of public-supply water sources in 2022 and the development of a geographic information system methodology for the Public Drinking Water Source Water Assessment Program in Tennessee
Introduction In 2021, the Tennessee Department of Environment and Conservation (TDEC) and the U.S. Geological Survey worked in cooperation to develop a geographic information system (GIS)-based methodology that systematically assesses the vulnerability of public-supply drinking water to potential contaminants consistent with the standards set forth in the Tennessee Source Water Assessment Program ( SWAP ) . As of June 2022, public-supply water was provided by 643 active public water systems across Tennessee that withdrew water for public use from 1,378 individual water sources. With the newly developed methodology , referred to as “TN- SWAPyT , ” TDEC can consistently delineate source water assessment zones and evaluate source susceptibility on the basis of information such as the proximity of contaminant sources, land-use activities, geologic information, and additional environmental spatial data. A major benefit of the TN- SWAPyT methodology is to provide TDEC with consistent reports that can be used as a starting point for assessing public supplies. Communities and public water systems can then build upon these reports by using local knowledge and site-specific information.
Tennessee↗
Lithium resource in the Smackover Formation brines of Southern Arkansas
Lithium-rich brine deposits occur throughout the United States, including in the Smackover Formation. The concentration of lithium in Smackover Formation brines was predicted across southern Arkansas by using a machine-learning model that incorporated lithium concentration data and geologic information. Between 5.1 and 19.0 million metric tons of lithium are calculated to be present in the brines of the Smackover Formation in southern Arkansas. The range in possible total lithium reflects the uncertainty in machine-learning predictions of lithium concentrations and the range of Smackover Formation porosity. This estimate quantifies the in-place lithium resource and does not consider the technological and economic feasibility of extracting the lithium from the brines.
Arkansas↗
Conceptualization and simulation of groundwater flow and groundwater availability in the Boone and Roubidoux aquifers in northeastern Oklahoma, 1980–2017
Oklahoma Groundwater Law (Oklahoma Statute § 82-1020.5) requires that the Oklahoma Water Resources Board conduct hydrologic investigations to determine the maximum annual yield for the State’s groundwater basins. The Boone and Roubidoux aquifers (also known as the Springfield Plateau aquifer and Ozark aquifer, respectively) are bedrock aquifers that extend from northeastern Oklahoma into Kansas, Arkansas, and Missouri. At present (2024), the Oklahoma Water Resources Board has yet to legally issue orders for the final determination of maximum annual yields for the Boone and Roubidoux aquifers. To support determination of a maximum annual yield, the U.S. Geological Survey, in cooperation with the Oklahoma Water Resources Board, developed a hydrogeologic framework, a conceptual groundwater-flow model, and a calibrated numerical groundwater-flow model for the Boone and Roubidoux aquifers. Three types of groundwater-availability scenarios were simulated by using the calibrated numerical model. These scenarios were used to (1) estimate equal-proportionate-share groundwater withdrawal rates (groundwater withdrawal applied equally over the aquifer), (2) quantify the potential effects of projected groundwater withdrawals on groundwater storage over a 50-year period, and (3) simulate the potential effects of a hypothetical 10-year drought. For the Boone aquifer, equal-proportionate-share groundwater withdrawal rates were 1.10, 0.98, and 0.96 acre-feet per acre per year for the 20-, 40-, and 50-year scenarios, respectively. For the Roubidoux aquifer, equal-proportionate-share groundwater withdrawal rates were 1.76, 1.34, and 1.25 acre-feet per acre per year for the 20-, 40-, and 50-year simulations, respectively. For the 50-year scenarios, stream seepage was minimally affected. Over the 10-year drought scenario, groundwater storage in the Boone and Roubidoux aquifers decreased by 660,451 acre-feet (6.7 percent) and 508,472 acre-feet (1.0 percent), respectively.
Oklahoma↗
Evaluation of the lithium resource in the Smackover Formation brines of southern Arkansas using machine learning
Global demand for lithium, the primary component of lithium-ion batteries, greatly exceeds known supplies, and this imbalance is expected to increase as the world transitions away from fossil fuel energy sources. High concentrations of lithium in brines have been observed in the Smackover Formation in southern Arkansas (>400 milligrams per liter). We used published and newly collected brine lithium concentration data to train a random forest machine-learning model using geologic, geochemical, and temperature explanatory variables and create a map of predicted lithium concentrations in Smackover Formation brines across southern Arkansas. Using these predicted lithium maps with reservoir parameters and geologic information, we calculated that there are 5.1 to 19 million tons of lithium in Smackover Formation brines in southern Arkansas, which represents 35 to 136% of the current US lithium resource estimate. Based on these calculations, in 2022, 5000 tons of dissolved lithium were brought to the surface within brines as waste streams of the oil, gas, and bromine industries.
Arkansas↗
Machine-learning predictions of groundwater specific conductance in the Mississippi Alluvial Plain, south-central United States, with evaluation of regional geophysical aerial electromagnetic data as explanatory variables
The Mississippi Alluvial Plain, located in the south-central United States, is undergoing long-term groundwater-level declines within the surficial Mississippi River Valley alluvial aquifer (hereinafter referred to as “alluvial aquifer”), which has raised concerns about future groundwater availability. In some parts of the alluvial aquifer, groundwater availability for common uses such as irrigation, public supply, and domestic use is limited by quality (for example, high salinity) rather than quantity of water stored in the aquifer. The Mississippi Alluvial Plain region has an abundance of water-quality measurements in the alluvial aquifer and deeper aquifers; however, large areas lack direct measurements of salinity to evaluate regional groundwater availability. Statistical models can interpolate between wells to fill in spatial data gaps. In 2021, the U.S. Geological Survey trained two boosted regression tree (BRT) machine-learning models on specific conductance data available between 1942 and 2020 to predict spatially continuous surfaces of groundwater salinity at multiple depths for the alluvial aquifer and deeper aquifers. Well construction information, water levels, and surficial variables such as geomorphology and soils were included as explanatory variables in this baseline model. Additionally, subsurface electrical resistivity data from the first aquifer-wide aerial electromagnetic (AEM) survey for the region were incorporated to create a geophysical model. This work expands on prior BRT salinity predictions of the alluvial aquifer and extends predictions south to the Gulf of Mexico, where groundwater salinity is high. AEM survey data were not available for the southern extent of the alluvial aquifer at the time of modeling. A BRT model was trained without (baseline) and with (geophysical) AEM variables to test the ability of the models to predict salinity where explanatory data are missing and response data are sparse. Additionally, model sensitivity to AEM survey data was evaluated to better understand how AEM variables influence specific conductance predictions. Model performance was improved with the addition of geophysical data, which added three-dimensional information, thereby improving salinity predictions at depth. Groundwater specific conductance predictions can help inform other geophysical investigations in the southern extent of the study area, where high groundwater specific conductance can obfuscate changes in aquifer sediment resistivity and could limit groundwater resources for agricultural, public supply, and domestic uses.
Scientific Investigations Report↗
Potentiometric surfaces (2013, 2015), groundwater quality (2010–15), and water-level changes (2011–13, 2013–15) in the Sparta-Memphis aquifer in Arkansas
The Sparta-Memphis aquifer, present across much of eastern Arkansas, is the second most used groundwater resource in the State, with the Mississippi River Valley alluvial aquifer being the primary groundwater resource. The U.S. Geological Survey, in cooperation with Arkansas Department of Agriculture-Natural Resources Division, Arkansas Geological Survey, Natural Resources Conservation Service, Union County Water Conservation Board, and the Union County Conservation District, collects groundwater data across the Sparta-Memphis aquifer extent in Arkansas. This report presents water-level data for measurements conducted during two time periods, January–May 2013 and January–June 2015, and discusses water-level altitude changes for the 2011–13 and 2013–15 periods in the Sparta-Memphis aquifer. Accompanying water-level data in this report include groundwater-quality data for the period 2010–15 in the Sparta-Memphis aquifer. Groundwater data can guide ongoing and future groundwater-monitoring efforts and inform management of the aquifers in Arkansas. Water levels measured at 306 wells from January to May 2013 and 273 wells from January to June 2015 are graphically presented as potentiometric-surface maps. Measurements from 2011, 2013, and 2015 were used in the construction of 2011–13 and 2013–15 water-level change maps. Select long-term hydrographs are included in the report to illustrate water-level changes at the local scale. Water-level data show the influence of climate, pumping, and conservation and management efforts on groundwater levels. With respect to climate, the study area experienced extreme drought conditions between January 2011 and December 2012. The proximate effects of drought—increased evapotranspiration, decreased recharge, and increased irrigation needs—resulted in water-level declines that were particularly notable in the northern and central portions of the study area. Groundwater sampled in 2010–15 from 148 wells completed in the Sparta-Memphis aquifer was analyzed for specific conductance, pH, chloride (Cl) concentration, and bromide (Br) concentration. In 2015, groundwater-quality data from 103 wells completed in the Sparta-Memphis aquifer had a median specific conductance of 356 microsiemens per centimeter at 25 degrees Celsius and a median Cl concentration of 9.5 milligrams per liter (mg/L). The data show two areas of higher Cl (greater than 10 mg/L) and higher Br (greater than 0.5 mg/L) concentrations in Union, Calhoun, and Bradley Counties in southern Arkansas and Monroe and Phillips Counties in eastern-central Arkansas. A Cl and Br mixing model indicates the two regions of wells may have different sources of higher salinity. In the greater Union County area, water in most wells may be a mixture of recharge or precipitation and higher salinity groundwater from the Nacatoch aquifer. Water in wells in eastern-central Arkansas may be sourced from aquifers having a higher Cl concentration (and thus, also a higher Cl-to-Br ratio).
Arkansas↗
Salinity and total dissolved solids measurements for natural waters: An overview and a new salinity method based on specific conductance and water type
The total concentration of dissolved constituents in water is routinely quantified by measurements of salinity or total dissolved solids (TDS). However, salinity and TDS are operationally defined by their analytical methods and are not equivalent for most waters. Furthermore, multiple methods are available to determine salinity and TDS, and these methods have inherent differences. TDS is defined as the mass of anhydrous residue remaining in a sample vessel after evaporation and subsequent oven drying at a defined temperature. Salinity is a measure of the mass of dissolved salts in a given mass of solution. In addition, there are approaches that quantify the total solute (TS) concentration, including gases. The purpose of this study is to develop a proxy method using specific conductance and major-ion water type to reliably predict salinity, TDS, and/or TS. Thus, we compared several methods to calculate salinity, TDS, and TS for 6391 surface water samples and conclude the following: TDS measurements are best suited for studies of anhydrous residue (e.g., evaporites); salinity determined by summing the speciated ion concentrations, termed S ∑spec , is the most comprehensive method to represent the concentration of dissolved constituents in natural waters; and TS determinations are useful if dissolved CO 2 and other gases are of interest. Thus, we utilized S ∑spec to compare differences between the various salinity, TDS, and TS methods, and to develop a new proxy method to predict salinity based on specific conductance (SC) and major ion water type, termed S SC_WT . For the surface waters used in this study, the median difference between TDS and S ∑Spec was between −19% and −24%, depending on the method. The median difference between S SC_WT and S ∑Spec was −2.4% for the samples in this study. The S SC_WT approach is cost effective, rapid, and capable of providing reliable real-time salinity determinations at surface water sites where SC data are available and water type is known.
Applied Geochemistry↗
System-scale airborne electromagnetic surveys in the lower Mississippi River Valley support multidisciplinary applications
The lower Mississippi River Valley spans over 200,000 square kilometres in parts of seven states, encompassing areas of critical groundwater supplies, natural hazards, infrastructure, and low-lying coastal regions. From 2018 - 2022, the U.S. Geological Survey acquired over 82,000 line-kilometres of airborne electromagnetic, radiometric, and magnetic data over this region to provide comprehensive and systematic information about subsurface geologic and hydrologic properties that support multiple scientific and societal interests. Most of the data were acquired on a regional grid of west-east flight lines separated by 3 - 6 kilometres; however, several high-resolution inset grids with line spacing as close as 200 m were acquired in targeted areas of interest. Approximately 8,000 line-kilometres were acquired along streams and rivers to characterise the potential for surface water-groundwater connection, and another 6,000 line-kilometres were acquired along the Mississippi and Arkansas River levees to characterise this critical infrastructure. Here, we present a summary of the data along with several examples of how they are being used to inform regional groundwater model development, inferences of groundwater salinity, identification of faults in the New Madrid seismic zone, and levee infrastructure.
lower Mississippi River Valley↗
Mapped predictions of manganese and arsenic in an alluvial aquifer using boosted regression trees
Manganese (Mn) concentrations and the probability of arsenic (As) exceeding the drinking-water standard of 10 μg/L were predicted in the Mississippi River Valley alluvial aquifer (MRVA) using boosted regression trees (BRT). BRT, a type of ensemble-tree machine-learning model, were created using predictor variables that affect Mn and As distribution in groundwater. These variables included iron (Fe) concentrations and specific conductance predicted from previously developed BRT models, groundwater flux and age estimates from MODFLOW, and hydrologic characteristics. The models also included results from the first airborne geophysical survey conducted in the United States to target an entire aquifer system. Predictions of high Mn and As occurred where Fe was high. Predicted high Mn concentrations were correlated with fraction of young groundwater (less than 65 years) computed from MODFLOW results. High probabilities of As exceedance were predicted where groundwater was relatively old and airborne electromagnetic resistivity was high, typically proximal to streams. Two-variable partial-dependence plots and sensitivity analysis were used to provide insight into the factors controlling Mn and As distribution in groundwater. The maps of predicted Mn concentrations and As exceedance probabilities can be used to identify areas where these constituents may be high, and that could be targeted for further study. This paper shows that incorporation of a selected set of process-informed data, such as MODFLOW results and airborne geophysics, into a machine-learning model improves model interpretability. Incorporation of process-rich information into machine-learning models will likely be useful for addressing a wide range of problems of interest to groundwater hydrologists.
Arkansas, Louisiana, Mississippi, Tennessee↗
Airborne geophysical surveys of the lower Mississippi Valley demonstrate system-scale mapping of subsurface architecture
The Mississippi Alluvial Plain hosts one of the most prolific shallow aquifer systems in the United States but is experiencing chronic groundwater decline. The Reelfoot rift and New Madrid seismic zone underlie the region and represent an important and poorly understood seismic hazard. Despite its societal and economic importance, the shallow subsurface architecture has not been mapped with the spatial resolution needed for effective management. Here, we present airborne electromagnetic, magnetic, and radiometric observations, measured over more than 43,000 flight-line-kilometers, which collectively provide a system-scale snapshot of the entire region. We develop detailed maps of aquifer connectivity and shallow geologic structure, infer relationships between structure and groundwater age, and identify previously unseen paleochannels and shallow fault structures. This dataset demonstrates how regional-scale airborne geophysics can close a scale gap in Earth observation by providing observational data at suitable scales and resolutions to improve our understanding of subsurface structures.
Mississippi River Valley↗
Machine-learning predictions of redox conditions in groundwater in the Mississippi River Valley alluvial and Claiborne aquifers, south-central United States
Machine-learning models developed by the U.S. Geological Survey were used to predict iron concentrations and the probability of dissolved oxygen (DO) concentrations exceeding a threshold of 1 milligram per liter (mg/L) in groundwater in aquifers of the Mississippi embayment physiographic region. DO and iron concentrations are driven by and reflect the oxidation-reduction (redox) conditions in groundwater. Predictions from boosted regression trees, a type of machine-learning model, of iron concentration and DO threshold probability were used to categorize redox zones in the Mississippi River Valley alluvial aquifer (MRVA), middle Claiborne aquifer (MCAQ), and lower Claiborne aquifer (LCAQ). Model predictions indicated that DO concentrations greater than 1 mg/L are uncommon across the MRVA. DO events (where the predicted probability was greater than 0.5) tended to occur on the margins of the MRVA and in upland areas where MCAQ and LCAQ units crop out at the surface or are at shallow depth. Predicted iron concentrations were higher in the MRVA than in the MCAQ and LCAQ. Uncertainty in predicted iron concentrations tended to be high in areas where measured concentrations were also high, resulting in small areas (encompassing less than 1.5 percent of the areal extent of the MRVA) of predicted iron concentrations that exceeded 100,000 micrograms per liter. Despite the large magnitude of overpredicted iron concentrations, the general proportion and spatial distribution of predicted iron concentrations reflected observed concentrations in groundwater wells. Where the probability of exceeding a DO concentration of 1 mg/L was 0.8 or more and the iron concentration was less than 1,000 micrograms per liter, aquifers were categorized as oxic. Oxic conditions were mostly in the uplands where MCAQ and LCAQ units crop out at the margins of the modeled area. The MRVA was mostly anoxic, which was controlled by DO threshold probabilities less than 0.1. The predictions and redox zones support conceptual models of redox conditions in the Mississippi embayment. The MRVA is predominantly anoxic with high iron concentrations. In the Claiborne aquifers (including the MCAQ and LCAQ), groundwater flows along regional flow paths toward the axis of the Mississippi embayment (the approximate location of the Mississippi River), the residence time in the aquifer increases, DO is consumed, and iron concentrations generally increase. Elevated concentrations of trace elements, such as manganese and arsenic, are often associated with reducing conditions in anoxic and mixed anoxic zones, but other factors such as sediment mineralogy affect the occurrence and distribution of these constituents.
Alabama, Arkansas, Kentucky, Louisiana, Mississipp↗
The impact of ventilation patterns on calcite dissolution rates within karst conduits
Erosion rates in streams vary dramatically over time, as differences in streamflow and sediment load enhance or inhibit erosion processes. Within cave streams, and other bedrock channels incising soluble rocks, changes in water chemistry are an important factor in determining how erosion rates will vary in both time and space. Prior studies in surface streams, springs, and caves suggest that variation in dissolved CO 2 is the strongest control on variation in calcite dissolution rates. However, the controls on CO 2 variation remain poorly quantified. Limited data suggest that ventilation of karst systems can substantially influence dissolved CO 2 within karst conduits. However, the interactions among cave ventilation, air-water CO 2 exchange, and dissolution dynamics have not been studied in detail. In this study, three years of time series measurements of dissolved and gaseous CO 2 , cave airflow velocity, and specific conductance from Blowing Springs Cave, Arkansas, were analyzed and used to estimate continuous calcite dissolution rates and quantify the correlations between those rates and potential physical and chemical drivers. We find that chimney effect airflow creates temperature-driven switches in airflow direction, and that the resulting seasonal changes in airflow regulate both gaseous and dissolved CO 2 within the cave. As in previous studies, partial pressure of CO 2 ( p CO 2 ) is the strongest chemical control of dissolution rate variability. However, we also show that cave airflow direction, rather than streamflow, is the strongest physical driver of changes in dissolution rate, contrary to the typical situation in surface channel erosion where floods largely determine the timing and extent of geomorphic work. At the study site, chemical erosion is typically active in the summer, during periods of cave downdraft (airflow from upper to lower entrances), and inactive in the winter, during updraft (airflow from lower to upper entrances). Storms provide only minor perturbations to this overall pattern. We also find that airflow direction modulates dissolution rate variation during storms, with higher storm variability during updraft than during downdraft. Finally, we compare our results with the limited set of other studies that have examined dissolution rate variation within cave streams and draw an initial hypothesis that evolution of cave ventilation patterns strongly impacts how dissolution rate dynamics evolve over the lifetime of karst conduits.
Arkansas, Missouri↗
Predicted pH of groundwater in the Mississippi River Valley alluvial and Claiborne aquifers, south-central United States
Regional aquifers in the Mississippi embayment are the principal sources of water used for public and domestic supply, irrigation, and industrial uses throughout the region. An understanding of how water quality varies spatially, temporally, and with depth are critical aspects to ensuring long-term sustainable use of these resources. A boosted regression tree (BRT) model was used by the U.S. Geological Survey (USGS) to map water quality in the three regional aquifers with the largest groundwater withdrawals in the embayment: the Mississippi River Valley alluvial (MRVA) aquifer, middle Claiborne aquifer (MCAQ), and lower Claiborne aquifer (LCAQ). The BRT model was used to predict pH to 1-kilometer raster grid cells for seven aquifer layers (one MRVA, four MCAQ, two LCAQ) following the hydrogeologic framework of the Mississippi embayment aquifer system regional MODFLOW model. The methods and approach used for pH predictions are the same as those used recently by the USGS to predict specific conductance and chloride in the aquifers. Explanatory variables for the BRT models included variables describing well location and construction, surficial variables such as soil properties and land use, and variables extracted from the groundwater flow model, such as groundwater levels and ages. The primary source of pH data was the USGS National Water Information System database. Additional data from State ambient groundwater monitoring programs and the Safe Drinking Water Information System also were used. For wells sampled multiple times, the most recent sample was used. Because groundwater residence times are long (greater than 100 years) throughout much of the study area, the possible effects of changes in water quality over time were considered small compared to the improvement in overall model accuracy by using available historical data. Values of pH from 3,362 wells for samples collected between 1960 and 2018 were used as training data for the BRT model. An additional 839 samples were used as holdout data to evaluate model performance. The predictive performance of the pH model is lower than for the training dataset, as indicated by an r-squared value of 0.89 for the training data and an r-squared of 0.71 for the holdout data. The root mean squared errors for the training and holdout data are 0.32 and 0.50 standard pH units, respectively. Data generated during this study and the model output are available from the companion data release.
Alabama, Arkansas, Louisiana, Mississippi, Missour↗
Using boosted regression tree models to predict salinity in Mississippi embayment aquifers, central United States
High salinity limits groundwater use in parts of the Mississippi embayment. Machine learning was used to create spatially continuous and three‐dimensional predictions of salinity across drinking‐water aquifers in the embayment. Boosted regression tree (BRT) models, a type of machine learning, were used to predict specific conductance (SC) and chloride (Cl), and total dissolved solids (TDS) was calculated from a correlation with SC. Explanatory variables for BRT models included well location and construction, surficial variables (e.g., soils and land use), and variables extracted from a groundwater‐flow model, including simulated groundwater ages. BRT model fits ( r 2 ) were 0.74 (SC and Cl) and 0.62 (TDS). BRT models provided spatially continuous salinity predictions across surficial and deeper aquifers where discrete water‐quality samples were missing. Uncertainty was smaller where salinity was lower, and models tended to underpredict in areas of highest salinity. Despite this, BRT models were able to capture areas of documented high salinity that exceed the TDS secondary maximum contaminant level for drinking water of 500 mg/L. Variables that served as surrogates for position along groundwater flowpaths were the most important predictors, indicating that much of the control on dissolved solids is related to rock‐water interaction as residence time increases. BRT models additionally support hypotheses of both surficial and deep sources of salinity.
Alabama, Arkansas, Kentucky, Louisiana, Mississipp↗
Groundwater availability in the Ozark Plateaus aquifer system
Executive Summary The study described in this report, initiated by the U.S. Geological Survey in 2014, was designed to evaluate fresh groundwater resources within the Ozark Plateaus, central United States, as an area within a broader national assessment of groundwater availability. The goals of the Ozark study were to evaluate historical effects of human activities on water levels and groundwater availability, quantify groundwater resources now and under probable future pumping and climate conditions, and evaluate existing monitoring networks for their value in making better predictions of future groundwater resources. Previous studies include simulation of local-scale groundwater flow under varying temporal scales, or simulation of the regional system under steady-state conditions. While these studies are useful, particularly for the problem for which they were designed, there is a need to look at the larger regional system under transient conditions to fully evaluate the water resource over time. This study focused on multiple spatial and temporal scales to examine changes in groundwater pumping, storage, and water-level declines. The regional scale provides a broad view of the sources and demands on the system with time. The study area covers approximately 68,000 square miles in the central United States in parts of Missouri, Arkansas, Kansas, and Oklahoma and encompasses the Ozark Plateaus Physiographic Province (Ozark Plateaus), including the Salem Plateau, Springfield Plateau, and Boston Mountains. Groundwater is withdrawn from the Ozark Plateaus aquifer system (Ozark system) for public supply and for domestic, agriculture (including irrigation and aquaculture), livestock, and non-agricultural use (including industrial, thermoelectric power generation, mining, and commercial). The Ozark system provides an important drinking-water supply for people living in the Ozark Plateaus because public supply and domestic use combined constitute the largest groundwater use. Precipitation is the ultimate source of freshwater to the Ozark system; most rainfall occurs during April, May, and June, and precipitation increases generally from north to south across the study area. Groundwater use currently accounts for only 10 percent of the total water use in the areas overlying the Ozark system, but provides a critical drinking-water resource because public supply and domestic groundwater withdrawals are largely from groundwater resources. The 380 million gallons per day of groundwater withdrawn from the Ozark system in 2010 accounts for approximately 2 percent of recharge. Although groundwater use represents a small component of the hydrologic budget, because of low storage in aquifer units, cones of depression with steep water-level gradients can develop quickly around pumping centers. The amount of water entering and leaving the aquifer system from 1900 to about 1965 was relatively constant at a rate of about 13 billion gallons per day (Bgal/d). Much of this inflow of water is discharged through streams in the system to balance the hydrologic budget. Changes in storage over time (from outflows to inflows) reflect the large variability in recharge: if recharge decreases, water levels will decrease, resulting in less groundwater discharge to streams and more water released from aquifer storage. Conversely, when recharge increases, water levels increase, more groundwater discharges to streams, and aquifer storage is replenished. Although pumping generally increased from 1900 to 2016, it does not appear to correlate with the change in storage over the same time period. Regionally, simulated change in groundwater storage corresponds with changes in recharge, more so than with increases in pumping. Average recharge was 11.6 Bgal/d for the period 1900 to 2016. Recharge was generally above average from predevelopment to 1965, followed by a period of below-average recharge from 1965 to about 1980. Recharge remained consistently above average from 1980 to about 1988, after which there was a period of average or below-average recharge, reflected by a decline through the mid-2000s. The implications and potential effects of increased pumping and long-term climate change on the Ozark Plateaus hydrologic system and groundwater availability are a concern for communities and resource managers in the area. Pumping varies from year to year, but is generally expected to moderately increase with population, industrial, and agricultural needs. Most climate models predict warmer minimum and maximum air temperatures by midcentury in the Ozark Plateaus area, especially from midspring through early fall. Three scenarios were developed to simulate possible future conditions from 2016 to 2060 and assess the potential effects on the hydrologic system and availability of water resources. For each scenario, changes in water levels and hydrologic budget components were evaluated from predevelopment (1900) to present (2016) and 45 years into the future (2060). The baseline scenario represents an extension of the average (1996 to 2016) seasonal pumping and recharge values. The pumping scenario is an extension of the average (1996 to 2016) seasonal recharge values with increases in pumping following the historical trend for the period 2016–2060 of up to 120 percent of the 1996 to 2016 average seasonal pumping values. The general circulation model (GCM) scenario is an extension of the average (1996 to 2016) seasonal pumping values and variable recharge based on seasonal averages of soil water storage from a water-balance model using temperature and precipitation from multiple GCMs. The general patterns of water-level decline are similar for each scenario. The areas of water-level decline in southwest Missouri and northeast Oklahoma are only marginally different by 2060 from those of 2009. In one area south of Springfield, Mo., water-level declines are less in the baseline and GCM scenarios than in 2009. This may be the result of a transition from groundwater use to surface-water supplies for a larger percentage of the demand in the area. For all three scenarios, forecasted pumping, recharge, and aquifer properties play an important role in determining the uncertainty of water-level forecasts at 94 real-time observation wells. Simulated aquifer properties in the productive middle and lower Ozark aquifers and the St. Francois confining unit of the Ozark system contribute most to predictive uncertainty in water levels at approximately 35 percent of the real-time observation wells. Out of the 94 real-time observation wells, 82 are developed in the lower Ozark aquifer.
Arkansas, Kansas, Missouri, Oklahoma↗